Particle Swarm Optimization-Based Extremum Seeking Control

This paper devises a particle swarm optimization-based extremum seeking control (ESC) scheme In the scheme the system states ate guided to the optimal point by the controller based on the output measurement, and the explicit form of the performance function is not needed By measuring the performance function value online, a sequence, generated by the particle swat in optimization algorithm, steels the regulator that chives the system states approaching to the set point that optimizes the performance We also propose an algorithm that fist reshuffles the sequence, and then inserts intermediate states into the sequence, to reduce the regulation gain and oscillation induced by stochastic population-based searching algorithms Simulation examples demonstrate the effectiveness and robustness of the proposed scheme